Summarize Test Results

Extract and summarize test results.

Usage

summarize_tests(
  object,
  collapse = c("none", "all_sig", "at_least_one_sig", "at_least_k_sig"),
  at_least_k = 1
)

# S3 method for class 'test_summary_list'
print(x, digits = 3, ...)

# S3 method for class 'test_summary'
print(x, digits = 2, ...)

# S3 method for class 'test_out_list'
print(x, digits = 3, test_long = FALSE, ...)

Arguments

object: A power4test object or the element test_all in a power4test object.
collapse: Whether a single decision (significant vs. not significant) is made across all tests for a test that consists of several tests (e.g., the tests of several parameters). If "none", tests will be summarized individually. If "all_sig", then the set of tests is considered significant if all individual tests are significant. If "at_least_one_sig", then the set of tests is considered significant if at least one of the tests is significant. If "at_least_k_sig", then the set of tests is considered significant if at least k tests are significant, k set by the argument at_least_k.
at_least_k: Used by collapse, the number of tests required to be significant for the set of tests to be considered significant.
x: The object to be printed.
digits: The numbers of digits after the decimal when printing numeric results.
...: Optional arguments. Not used.
test_long: If TRUE, a detailed report will be printed.

Value

The function summarize_tests() returns a list of the class test_summary_list. Each element contains a summary of a test stored. The elements are of the class test_summary, with these elements:

test_attributes: The stored information of a test, for printing.
nrep: The number of datasets (replications).
mean: The means of numeric information. For significance tests, these are the rejection rates.
nvalid: The number of non-NA replications used to compute each mean.

The print methods returns x invisibly. They are called for their side effects.

Details

The function summarize_tests() is used to extract information from each test stored in a power4test object.

The method print.test_out_list() is used to print the content of a list of test stored in a power4test object, with the option to print just the names of tests.

The role of `summarize_tests()` and related functions

The function summarize_tests() and related print methods are used by the all-in-one function power4test() and its summary method. Users usually do not call them directly, though developers can use this function to develop other functions for power analysis, or to build their own workflows to do the power analysis.

Examples


# Specify the model

mod <-
"
m ~ x
y ~ m + x
"

# Specify the population values

es <-
"
y ~ m: l
m ~ x: m
y ~ x: n
"

# Simulated datasets

sim_only <- power4test(nrep = 2,
                       model = mod,
                       pop_es = es,
                       n = 100,
                       do_the_test = FALSE,
                       iseed = 1234)
#> Simulate the data:
#> Fit the model(s):

# Test the parameters in each dataset

test_out <- power4test(object = sim_only,
                       test_fun = test_parameters)
#> Do the test: test_parameters: CIs  

# Print the summary

summarize_tests(test_out)
#> 
#> =============== <test_parameters: CIs > ===============
#> 
#> Mean(s) across replication:
#>   test_label lhs op rhs    est    se      z pvalue   cilo  cihi   sig
#> 1        m~x   m  ~   x  0.382 0.103  3.698  0.000  0.179 0.585 1.000
#> 2        y~m   y  ~   m  0.443 0.094  4.715  0.000  0.259 0.627 1.000
#> 3        y~x   y  ~   x -0.029 0.104 -0.226  0.236 -0.232 0.174 0.000
#> 4       m~~m   m ~~   m  0.945 0.134  7.071  0.000  0.683 1.207 1.000
#> 5       y~~y   y ~~   y  0.836 0.118  7.071  0.000  0.604 1.068 1.000
#> 
#> - The column 'sig' shows the rejection rates.
#> - If the null hypothesis is false, the rate is the power.
#> - Number of valid replications for rejection rate(s): 2 
#> - Proportion of valid replications for rejection rate(s): 1.000